本文選題：分布式電源 + 多目標免疫克隆算法　； 參考：《長沙理工大學》2014年碩士論文

【摘要】：分布式電源由于其具有發(fā)電方式靈活、建設周期短、污染排放少等優(yōu)點得到了迅速發(fā)展。然而,隨著分布式電源大量接入配電網(wǎng),其接入位置和容量對電力系統(tǒng)的網(wǎng)絡損耗、電壓分布、可靠性和系統(tǒng)保護都產(chǎn)生了很大的影響,因此,研究如何更合理地規(guī)劃分布式電源對實現(xiàn)配網(wǎng)系統(tǒng)安全經(jīng)濟運行具有重要意義。論文首先闡述了分布式發(fā)電的研究意義和發(fā)展狀況,在綜述了分布式電源規(guī)劃研究現(xiàn)狀的基礎(chǔ)上,對多種分布式發(fā)電技術(shù)及其對配電網(wǎng)的影響進行了較詳細的分析；針對風力發(fā)電和光伏發(fā)電出力不穩(wěn)定以及負荷波動的特點,提出了考慮其時序特性的分布式電源規(guī)劃模型；在研究了多種分布式電源出力特性的基礎(chǔ)上,采用儲能裝置平滑風電和光伏發(fā)電出力的波動；進而建立了兼顧系統(tǒng)運行經(jīng)濟性和穩(wěn)定性以及環(huán)境因素的多目標規(guī)劃模型；采用多目標免疫克隆算法進行模型求解,該算法采用整體克隆非支配抗體、非一致性變異和刪除帕累托(Pareto)前端密集解的策略來保證收斂速度和解的均勻性與寬廣性；通過三個經(jīng)典的測試函數(shù),運用三個性能指標對算法進行評價,同時與改進非劣分層遺傳算法和改進強度帕累托進化算法兩種經(jīng)典多目標算法進行比較,驗證多目標免疫克隆算法的優(yōu)越性。采用IEEE33節(jié)點的配電網(wǎng)系統(tǒng)進行算例仿真分析,將多目標免疫克隆算法與改進非劣分層遺傳算法的求解結(jié)果進行比較分析,驗證了多目標免疫克隆算法求解分布式電源規(guī)劃模型的有效性。論文所建的規(guī)劃模型考慮了多種分布式電源出力與負荷的不穩(wěn)定性,使得規(guī)劃結(jié)果更接近于實際,具有一定的實用價值與指導意義。
[Abstract]:Because of its advantages of flexible power generation mode, short construction period and less pollution emission, distributed power generation has been developed rapidly. However, with a large number of distributed power sources connected to the distribution network, its access position and capacity have a great impact on the network loss, voltage distribution, reliability and system protection of the power system. It is very important to study how to plan the distributed power supply more reasonably to realize the safe and economical operation of distribution network system. Firstly, the research significance and development status of distributed generation are described in this paper. On the basis of summarizing the present situation of distributed generation planning, various distributed generation technologies and their effects on distribution network are analyzed in detail. According to the characteristics of instability and load fluctuation of wind power generation and photovoltaic power generation, a distributed power generation planning model considering its timing characteristics is proposed. The energy storage device is used to smooth the fluctuation of wind power and photovoltaic power generation, and then a multi-objective programming model considering the economic and stability of the system as well as environmental factors is established, and the multi-objective immune clone algorithm is used to solve the model. The algorithm adopts the strategy of global cloning of non-dominant antibodies, inconsistency mutation and deletion of Pareto-Pareto front-end dense solutions to ensure convergence speed and uniformity and broadness, and through three classical test functions, Three performance indexes are used to evaluate the algorithm, and compared with the improved non-inferior hierarchical genetic algorithm and the improved strength Pareto evolutionary algorithm, the superiority of the multi-objective immune clone algorithm is verified. The simulation analysis of distribution network system with IEEE 33 node is carried out, and the results of multi-objective immune clone algorithm and improved non-inferior hierarchical genetic algorithm are compared and analyzed. The effectiveness of the multi-objective immune clone algorithm for solving the distributed power planning model is verified. The planning model proposed in this paper takes into account the instability of the output and load of various distributed power sources, which makes the planning results closer to the actual situation, and has certain practical value and guiding significance.
【學位授予單位】：長沙理工大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TM715

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本文編號：1982471